Retrieval-augmented generation for large language models: A survey
Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …
challenges in practical applications, such as hallucinations, slow knowledge updates, and …
Large language models for information retrieval: A survey
As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …
search engines, have integrated themselves into our daily lives. These systems also serve …
Large legal fictions: Profiling legal hallucinations in large language models
Do large language models (LLMs) know the law? LLMs are increasingly being used to
augment legal practice, education, and research, yet their revolutionary potential is …
augment legal practice, education, and research, yet their revolutionary potential is …
Crud-rag: A comprehensive chinese benchmark for retrieval-augmented generation of large language models
Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of
large language models (LLMs) by incorporating external knowledge sources. This method …
large language models (LLMs) by incorporating external knowledge sources. This method …
Dense x retrieval: What retrieval granularity should we use?
Dense retrieval has become a prominent method to obtain relevant context or world
knowledge in open-domain NLP tasks. When we use a learned dense retriever on a …
knowledge in open-domain NLP tasks. When we use a learned dense retriever on a …
Personal llm agents: Insights and survey about the capability, efficiency and security
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have
been one of the key technologies that researchers and engineers have focused on, aiming …
been one of the key technologies that researchers and engineers have focused on, aiming …
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature
Recent advancements in large language models (LLMs) have achieved promising
performances across various applications. Nonetheless, the ongoing challenge of …
performances across various applications. Nonetheless, the ongoing challenge of …
Generate-then-ground in retrieval-augmented generation for multi-hop question answering
Multi-Hop Question Answering (MHQA) tasks present a significant challenge for large
language models (LLMs) due to the intensive knowledge required. Current solutions, like …
language models (LLMs) due to the intensive knowledge required. Current solutions, like …
Astute rag: Overcoming imperfect retrieval augmentation and knowledge conflicts for large language models
Retrieval-Augmented Generation (RAG), while effective in integrating external knowledge to
address the limitations of large language models (LLMs), can be undermined by imperfect …
address the limitations of large language models (LLMs), can be undermined by imperfect …
Rankrag: Unifying context ranking with retrieval-augmented generation in llms
Large language models (LLMs) typically utilize the top-k contexts from a retriever in retrieval-
augmented generation (RAG). In this work, we propose a novel instruction fine-tuning …
augmented generation (RAG). In this work, we propose a novel instruction fine-tuning …